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Record W4411547890 · doi:10.1017/9781009578103.006

Dull Instead of Light

2025· book-chapter· en· W4411547890 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2025
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Chapter 5, Dull Instead of Light, examines regular practitioners’ increasing efforts to disambiguate “medicine” and “quackery” in the wake of the 1868 formulation of the Hicklin test of obscenity. The first section explores how medical groups experimented with using obscenity laws as alternatives to the Medical Act (1858) to regulate medical practice. These actions’ impact on the book trade is debatable, but regular practitioners’ tireless efforts to collapse quackery and obscenity influenced new legislation governing medical advertising. The rest of the chapter examines parallel efforts to professionalize medical publishing. In advocating for limitations on medical book advertising, the use of dry, technical language in medical writing, and other changes to medical print culture, regular practitioners further sought to disambiguate “medicine” from “quackery.” The lines between popular and professional medical works had previously been blurry. The changes examined in this chapter helped cleave a growing chasm between the kinds of sexual knowledge accessible to medical and non-medical audiences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.009
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0320.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.184
Teacher spread0.152 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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